A Unified Alternating Direction Method of Multipliers by Majorization Minimization

Accompanied with the rising popularity of compressed sensing, the Alternating Direction Method of Multipliers (ADMM) has become the most widely used solver for linearly constrained convex problems with separable objectives. In this work, we observe that many existing ADMMs update the primal variable...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2018-03, Vol.40 (3), p.527-541
Hauptverfasser:	Lu, Canyi, Feng, Jiashi, Yan, Shuicheng, Lin, Zhouchen
Format:	Artikel
Sprache:	eng
Schlagworte:	Compressed sensing Computer vision Convergence convex optimization Jacobian matrices majorization minimization Minimization mixed ADMM Multipliers Optimization Radio frequency Unified frameworks of ADMM
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